1101
The Journal of Experimental Biology 212, 1101-1105
Published by The Company of Biologists 2009
doi:10.1242/jeb.026815
Individually variable energy management during egg production is repeatable across
breeding attempts
Tony D. Williams1,*, François Vézina1,† and John R. Speakman2
1
Department of Biological Sciences, Simon Fraser University, 8888 University Drive, Burnaby, Canada, V5A 1S6 and 2Aberdeen
Centre for Energy Regulation and Obesity (ACERO), Institute of Biological and Environmental Sciences, University of Aberdeen,
Aberdeen, AB24 2TZ, UK
*Author for correspondence (e-mail: tdwillia@sfu.ca)
Present address: Department of Biology, Universite de Quebec a Rimouski, 300 Allee Ursulines, Rimouski, Quebec, Canada, G5L 3A1
†
Accepted 28 January 2009
SUMMARY
It is axiomatic that whole-animal metabolism, measured for example as daily energy expenditure (DEE), plays a central role in
determining reproductive success and survival (fitness) in all organisms. Nevertheless, strong evidence for consistent systematic
relationships between DEE and either individual traits (age, sex, body size), environmental factors (e.g. food availability,
temperature) or ‘fitness’ traits (e.g. number of offspring, survival) remains far from compelling in birds and mammals. Recently,
we suggested that female birds might utilise complex, individually variable energy management strategies to meet the metabolic
demands of reproduction, generating a wide spectrum of effects on reproductive DEE, from overcompensation (net decrease in
DEE) to additive effects (net increase in DEE). Here we show that this individually variable adjustment or ‘plasticity’ in energy
expenditure associated with egg production is repeatable among individuals between successive breeding attempts in female
zebra finches (Taeniopygia guttata). Our study highlights the importance (a) of measuring ‘plasticity’ or change associated with
transitions of physiological state (e.g. non-breeding to breeding) based on multiple measurements of the same individual, and (b)
of extending consideration of how selection might drive the evolution of phenotypic plasticity per se to include physiological and
metabolic traits.
Key words: daily energy expenditure, energy management, inter-individual variation, plasticity, egg production, Taeniopygia guttata
INTRODUCTION
Whole-animal metabolism, measured for example as daily energy
expenditure (DEE), is widely assumed to play a central role in
determining reproductive success and survival, i.e. fitness, in all
organisms (Carey, 1996; Speakman, 2008). High energy demands
might constrain current reproduction because the supply of energy
during single breeding attempts is limited or they might generate
negative effects on future reproduction (Stearns, 1992). Thus, if
parental investment during reproduction is energetically costly then
individuals capable of sustaining higher levels of energy expenditure
should be better at reproducing, e.g. they may have larger clutch or
litter size or rear more offspring (e.g. Meijer et al., 1989; Rogowitz,
1998; Hammond et al., 1994; Tinbergen and Dietz, 1994; Speakman
and Krol, 2005). Despite the intuitive logic of these predictions,
evidence for consistent systematic relationships between DEE and
individual traits (age, sex, body size), environmental factors (e.g. food
availability, temperature) or reproductive- or fitness-related traits (e.g.
number of offspring, survival) is far from compelling in birds
(Williams and Vézina, 2001) (but see Sanz and Tinbergen, 1999; Fyhn
et al., 2001) and mammals (Speakman et al., 2003; Speakman, 2008)
[except for relationships with temperature (Speakman, 2000; Anderson
and Jetz, 2005)]. One reason for this might be the marked, and largely
unexplained, inter-individual variation in energy expenditure seen
within any population (e.g. Speakman et al., 1994; Berteaux et al.,
1996; McKechnie, 2008; Careau et al., 2008).
Recently, we suggested that female birds might utilise complex,
individually variable energy management strategies to meet the
metabolic demands of egg production (Vézina et al., 2006). At the
individual level, energy investment in egg production in female zebra
finches Taeniopygia guttata [i.e. increased resting metabolic rate,
RMR (Nilsson and Raberg, 2001; Vézina and Williams, 2005)]
generated a wide spectrum of effects on DEE, from overcompensation
(net decrease in DEE) to additive effects [net increase in DEE (Vézina
et al., 2006)]. Although all individuals appeared to compensate for
the cost of producing eggs via behavioural adjustments [decreased
locomotor activity (Vézina et al., 2006)] (see also Houston et al., 1995;
Williams and Ternan, 1999), this was individually variable.
Consequently, net increases in DEE were associated with relatively
high reproductive effort (large increase in RMR) and individuals with
low reproductive effort (small increase in RMR) were much better
at avoiding this cost, and in some cases even overcompensated for
the elevated RMR via these behavioural adjustments (Vézina et al.,
2006). We proposed that this inter-individual variation might help
explain why so few studies of free-living birds have found support
for positive relationships between energy expenditure and putative
correlated ecological or reproductive variables (Williams and Vézina,
2001), and why some studies report contradictory results in different
years (e.g. Stevenson and Bryant, 2000). Similarly, this may explain
the lack of systematic intraspecific relationships between resting or
basal metabolism and reproductive performance reported in many
studies in mammals (Hayes et al., 1992; Johnson et al., 2001; Krol
et al., 2003; Speakman et al., 2004; Johnston et al., 2007) and birds
(Williams and Vézina, 2001) (see also Blackmer et al., 2005). Here
we show that the marked inter-individual variation in the adjustment
(or ‘plasticity’) in DEE associated with egg production in female zebra
finches is repeatable, i.e. energy management strategies are not only
highly variable but are also consistent within individuals over multiple
breeding attempts.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
1102 T. D. Williams, F. Vézina and J. R. Speakman
MATERIALS AND METHODS
Zebra finches, Taeniopygia guttata Vieillot 1817, were maintained
in controlled environmental conditions as previously described
(Vézina et al., 2006). All birds received a mixed-seed diet (Panicum
and white millet, 50:50), water, grit and cuttlefish bone (calcium)
ad libitum, and egg-laying birds received 6 g of egg food supplement
(20.3% protein, 6.6% lipid) daily, which was always completely
consumed by the following day. In the present experiment (hereafter
termed trial 2) we formed pairs (single-sex and breeding; see below)
using a sub-sample of the individual females that we studied
previously [(Vézina et al., 2006) hereafter termed trial 1] and
measured locomotor activity, food intake and reproductive effort
during a second, repeated cycle of egg laying. Repeat measurement
of breeding birds in trial 2 occurred 7 months after trial 1. Six males
died between the two trials and so six females in trial 2 were paired
with different mates. However, this only affected one measured trait:
food intake (see Results). Birds were housed in cages
(61 cm⫻46 cm⫻41 cm) provided with an external nest box
(15 cm⫻14.5 cm⫻20 cm); for single-sex pairs access to the nest box
was blocked with cardboard. During the breeding experiment, nest
boxes were checked daily between 10:00 h and 12:00 h, and all new
eggs were weighed (to 0.001 g) and numbered. A clutch was
considered complete after two consecutive days with no new eggs.
All experiments and animal husbandry were carried out under a
Simon Fraser University Animal Care Committee permit (692B94), following the guidelines of the Canadian Committee on Animal
Care.
Our investigation of DEE adjustments associated with egg
production in zebra finches used a repeated measures approach to
compare DEE values of 22 females measured as non-breeders in
single-sex pairs and at the one-egg stage of laying (sample sizes,
non-breeders N=22, one-egg stage N=22). All birds used in the
experiment were first paired as single-sex, non-breeding female
pairs. Food consumption and locomotor activity (see below) were
measured on day 5, 6 and 7 of the single-sex period, and DEE was
measured from day 6 to day 7 using the doubly labelled water (DLW)
technique (see below). On day 8, all birds were rearranged into
breeding pairs and were given access to the nest boxes. Locomotor
activity was monitored starting the following day until clutch
completion. Food intake data were recorded the first 2 days after
pairing (pre-laying) and again during laying beginning the day prior
to laying of the first egg and during the following 4 days. All females
had their DEE measured at the one-egg stage (i.e. on the day they
laid their first egg) with estimates including a complete ovulation
and laying cycle (second egg).
We monitored locomotor activity by using a micro-switch system
connected to a cage perch as described previously (Williams and
Ternan, 1999; Vézina et al., 2006). Food intake was determined by
giving the birds 25 g day–1 of seeds in an open 946 ml ZiplocTM food
container placed on the cage floor and weighing the seeds remaining
in the container after 24 h. Williams and Ternan showed that, on
average, females eat slightly more food (4.5%) than males and that
this sex effect is significant only on the 2 days preceding the first
egg laid [P=0.016 and P=0.052, respectively, in their table 1
(Williams and Ternan, 1999)]. Food intake per pair is therefore a
good indicator of female food intake in our experimental context,
and we report the pair values (g pair–1 day–1) as representative of
female energy input, as the proportion of seeds eaten by both sexes
remains virtually unchanged throughout our experimental protocol
(for details, see Vézina et al., 2006).
We measured DEE using the DLW technique (Lifson and
McClintock, 1966; Speakman, 1998) as described before (Vézina
et al., 2006). This method has been previously validated by
comparison to indirect calorimetry in a range of birds (e.g. Bevan
et al., 1995; Visser and Shekkermann, 1999; van Tright et al., 2002).
On day one, the animals were weighed (±0.01 g) and a known mass
of DLW (ca. 67.7% 18O, 32.2% 2H) was administered (i.m.,
0.4 g 100 g–1 body mass). Syringes were weighed before and after
administration (±0.0001 g, Sartorius balance) to calculate the mass
of DLW injected. Blood samples were taken after 1 h of isotope
equilibration to estimate initial isotope enrichment (Krol and
Speakman, 1999). Blood samples were immediately heat sealed
into 2⫻50 ml glass capillaries, which were stored at 4°C. Samples
were also collected from unlabelled birds to evaluate the
background isotope enrichments of 2H and 18O [method C
(Speakman and Racey, 1987)]. Animals were recaptured and bled
24 h post-dosing to estimate isotope elimination rates. Capillaries
that contained the blood samples were then vacuum distilled (Nagy,
1983), and water from the resulting distillate was used to produce
CO2 and H2 [methods described in Speakman et al. for CO2
(Speakman et al., 1990) and in Speakman and Krol for H2
(Speakman and Krol, 2005)]. CO2 production was converted into
energy utilisation using a conversion factor of 24.03 J ml–1 CO2,
derived from the Weir equation (Weir, 1949) for a respiratory
quotient of 0.85. The isotope ratios 18O:16O and 2H:1H were
analysed using gas source isotope ratio mass spectrometry (Optima,
Micromass IRMS and Isochrom mG, Manchester, UK). We ran
three high enrichment standards each day alongside the samples
and corrected all the raw data to these standards. Isotope enrichment
was converted to values of DEE using a single pool model as
recommended for this size of animal (Speakman, 1993). There are
several alternative approaches for the treatment of evaporative water
loss in the calculation (Visser and Schekkermann, 1999). We chose
the assumption of a fixed evaporation of 25% of the water flux
[equation 7.17 in Speakman (Speakman, 1997)] which has been
established to minimise error in a range of conditions (Visser and
Schekkerman, 1999; van Tright et al., 2002).
Data were analysed using SAS software (version 9.1, 2002–2003;
SAS Institute, Cary, NC, USA). We measured multiple traits at
multiple times but had a relatively small sample size (N=22 females)
so we did not have sufficient power to analyse data in a single
comprehensive, multivariate analysis. We focused our analyses on
the change in DEE (ΔDEE), and variability in ΔDEE between trials
in egg-laying birds (i.e. between pre-laying and the one-egg stage),
as a comprehensive within-trial analysis with a larger sample size
has been reported previously (Vézina et al., 2006). We first
compared differences in mean trait values between trial 1 and trial
2, i.e. a ‘time’ effect, using repeated measures ANOVA, or
ANCOVA with relevant covariates (GLM procedure; see Results).
We calculated repeatability for each trait following Lessells and
Boag (Lessells and Boag, 1987), using the intraclass correlation
coefficient based on variance components derived from a one-way
ANOVA. We then analysed correlates of DEE in egg-laying birds
during trial 2 only [in order to confirm results previously reported
for trial 1 (Vézina et al., 2006)]. Finally, we compared individual
variation in ΔDEE between trials to between-trial differences in all
measured traits using correlation analysis.
RESULTS
Variation in body mass and reproductive traits
Female body mass was significantly higher in trial 2 in non-breeding
(single-sex) birds (F1,21=16.97, P<0.01), at pairing (F1,21=9.01,
P<0.01) and at the one-egg stage of laying (F1,21=12.92, P<0.01;
Table1) compared with values from trial 1: by 4.9%, 4.4% and 2.7%,
THE JOURNAL OF EXPERIMENTAL BIOLOGY
Repeatability of energy management
respectively. Body mass was highest at the one-egg stage but change
in body mass did not differ between trials either for the non-breeding
to pre-laying stage (P>0.20) or for the pre-laying to one-egg stage
(P>0.15). There was no difference in mean laying interval (time
between pairing and first egg, F1,21=0.70, P>0.4) or mean clutch
size (F1,21=0.06, P>0.8) between trials. Absolute egg mass was 4%
larger in trial 2 (F1,21=19.7, P<0.001; Table 1) but there was no
difference in mean egg mass between trials controlling for female
body mass (F1,21=1.60, P>0.2). Female body mass at the one-egg
stage, change in mass between the pre-laying and one-egg stage,
mean egg mass and clutch size were all repeatable traits (Table 1);
however, non-breeding mass and change in mass from the nonbreeding to pre-laying stage were not repeatable (P>0.05).
Variation in food intake and locomotor activity
Pre-laying food intake was significantly higher in trial 2 than in
trial 1, by 0.72 g (23%; F1,17=8.95, P<0.01). At the one-egg stage
there was a significant male effect and male⫻trial interaction for
food intake (both P<0.025). For females paired with the same male
there was no difference in food intake between trials (F1,15=0.55,
P>0.4). For females paired with different males there was a
marginally significant difference in food intake: 4.5 vs 5.7 g day–1
in trial 1 and trial 2, respectively (F1,5=5.38, P=0.068). However,
on average for all pairs food intake was only 3.1% higher during
trial 2 compared with trial 1 (F1,21=0.64, P>0.4) and food intake
was repeatable between trials (Table 1).
In both trials there was a marked decrease in locomotor activity
between the pre-laying and one-egg stage: trial 1, 1385±203 vs
854±89 hops day–1 (F1,20=13.75, P<0.01); trial 2, 1426±221 vs
640±67 hops day–1 (F1,20=14.09, P<0.01). Locomotor activity did
not differ among trials during pre-laying (F1,20=0.02, P>0.8), but
activity was lower during trial 2 in laying birds (F1,20=4.59, P=0.05).
For both single-sex pairs and breeding pairs activity during the 24 h
DEE measurement period was highly correlated (R≥0.76, P<0.001)
with activity measured over the whole time period (2–4 days).
Variation in DEE and ΔDEE
Non-breeding DEE, measured in single-sex pairs, was significantly
higher (by 10.5%) in trial 2 compared with trial 1 (F1,21=12.86,
P<0.01). However, controlling for body mass, this difference was
not significant (F1,25.7=1.17, P>0.2). Furthermore, there was no
difference in either absolute (F1,21=0.42, P>0.5) or mass-corrected
DEE (F1,22=0.37, P>0.5) between trials at the one-egg stage.
1103
In trial 2, one-egg DEE was positively correlated with food intake
(R22=0.58, P<0.01), and individuals with high one-egg DEE tended
to have larger eggs (R22=0.36, P=0.097) and show a larger increase
in body mass between the non-breeding and one-egg stage
(R22=0.37, P=0.087). However, one-egg DEE was independent of
locomotor activity, body mass, change in body mass (from nonbreeding to laying) and other measures of primary reproductive
output (laying interval, clutch size; P>0.15 in all cases).
ΔDEE in individual females associated with egg production
(calculated as one-egg DEE–non-breeding DEE, where a positive
value indicates a net increase in DEE during laying) was not
significant for either trial (trial 1, t22=1.90, P>0.05; or trial 2,
t22=0.56, P>0.5), i.e. on average DEE was not different for nonbreeding or one-egg birds (Fig. 1). However, in both trials there was
marked individual variation in ΔDEE between the non-breeding and
one-egg stages (Fig. 1B). In trial 1, ΔDEE varied between –17.3
and +24.1kJday–1 (–27.0% to +65.9% relative to non-breeding DEE)
and in trial 2 ΔDEE varied between –17.7 and +11.8 kJ day–1
(–30.8% to +23.3%). Both one-egg DEE and ΔDEE were repeatable
(Table 1; Fig. 1). Finally, the difference in ΔDEE between trials
(where negative values indicate greater ‘compensation’, i.e. lower
DEE or smaller increase in DEE relative to non-breeding values)
was independent of the difference in all measured traits between
trials (body mass, activity, food intake, reproductive effort).
DISCUSSION
In the present study we have shown that not only is absolute DEE
repeatable during egg production in female zebra finches, consistent
with other studies (for a review, see Nespolo and Franco, 2007),
but also the individually variable adjustment or ‘plasticity’ in energy
expenditure associated with egg production is consistent or
repeatable. The present study also confirms the key results of our
previous study (Vézina et al., 2006), namely that there is no change
in mean DEE associated with egg production in female zebra finches,
comparing non-breeding birds with birds at the one-egg stage of
laying, but that this masks marked, systematic inter-individual
variation in the change in DEE which we suggest indicates
individually variable energy management ‘strategies’. Although it
is clear that there are significant energetic costs associated with egg
production (e.g. Ward, 1996; Nilsson and Raberg, 2001; Vézina et
al., 2006) females appear to use behavioural mechanisms to
modulate these energetic costs. However, our study suggests that
individual females do this to varying degrees such that some females
Table 1. Primary reproductive effort, body mass, food intake (g pair–1 day–1), locomotor activity and daily energy expenditure during egglaying, and repeatability estimates for these traits
Parameter
Laying interval (days)
Clutch size
Mean egg mass (g)
One-egg body mass (g)
ΔBody mass (g)
Food intake (g pair–1 day–1)
Activity (hops day–1)
Non-breeding DEE (kJ day–1)
Laying DEE (kJ day–1)
ΔDEE (kJ day–1)
Trial 1
Trial 2
Difference
Repeatability
7.4±2.9
5.7±1.8
1.033±0.083
15.0±0.9
1.36±0.62
5.40±1.2
854±412
51.3±6.5
55.0±6.3
3.6±9.0
6.7±3.1
5.8±1.4
1.076±0.091
15.4±0.7
1.16±0.46
5.57±0.75
640±309
56.7±5.0
55.9±7.7
–0.79±6.32
n.s.
n.s.
P<0.001
P<0.01
n.s.
P=0.05
P=0.05
P<0.01
n.s.
P<0.01
n.s.
0.412*
0.762***
0.675***
0.422*
0.422*
0.797***
n.s.
0.569**
0.475**
Measurements were obtained from N=22 female zebra finches during two successive breeding attempts. Repeatability estimates were made following Lessells
and Boag (Lessells and Boag, 1987).
Change in body mass was calculated as the pre-laying mass minus the laying mass. Change in DEE (daily energy expenditure) was calculated as one-egg
DEE minus non-breeding DEE.
Values are means ± s.d.; *P<0.05, **P<0.01, ***P<0.001; n.s., not significant.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
1104 T. D. Williams, F. Vézina and J. R. Speakman
One-egg DEE (kJ day–1) – trial 2
80
A
70
60
50
40
40
50
60
70
80
–1
One-egg DEE (kJ day ) – trial 1
30
ΔDEE (kJ day–1) – trial 2
B
20
10
0
–10
–20
–20
–10
0
10
20
30
ΔDEE (kJ day–1) – trial 1
Fig. 1. Repeatability of (A) absolute daily energy expenditure (DEE) at the
one-egg stage, and (B) change in DEE (ΔDEE) between the non-breeding
and one-egg stage in female zebra finches measured in two successive
breeding trials.
‘overcompensate’ for these changes with a decrease in DEE during
egg production whereas other females incur additive costs with a
net increase in DEE during egg production.
So far we have been unable to resolve the cause of the marked
inter-individual variation in DEE or changes in DEE associated with
egg production, and this is likely to prove difficult given the potential
for (a) behavioural adjustments allowing reallocation of energy
among different activities (e.g. Williams and Ternan, 1999;
Speakman et al., 2001; Husak, 2006); (b) intrinsic physiological
adjustments such as organ remodelling (Vézina and Williams, 2003;
Speakman, 2008) or reallocation of energy away from other
physiological systems (e.g. Roberts et al., 2004; French et al., 2007);
and (c) effects of extrinsic factors such as ecological or social context
(Speakman et al., 2003). In the present study the only trait that was
strongly correlated with DEE was food intake (see also Vézina et
al., 2006). In our opinion this is probably an effect, rather than a
cause, of higher energy expenditure, i.e. birds have to increase
dietary intake to meet the higher DEE (although it is possible that
higher processing costs associated with increased food intake might
increase basal metabolic rate (BMR) (Nilsson, 2002) which might
in turn contribute to increased DEE (but see Williams and Vézina).
We previously reported (Vézina et al, 2006) that females with the
highest DEE at the one-egg stage produced larger clutches and
suggested that these females might benefit in terms of reproductive
investment despite the ‘additive’ nature of reproductive energy costs.
We could not confirm the relationship between DEE and clutch size
in the present study, although there was some evidence to support
the idea that individuals with the highest one-egg DEE obtain
benefits in terms of reproductive output: there was a trend for DEE
to be associated with a larger egg size and a larger change in body
mass, perhaps reflecting a higher mass of developing reproductive
organs (Vézina et al., 2006). By definition, repeatability is typically
calculated using repeat measurements of individuals under similar
conditions, as in this experiment, and if DEE is mainly set by
extrinsic factors such as food supply (which was constant and ad
libitum in our experiment) then this might overestimate repeatability
related to intrinsic factors (Speakman, 2000; Speakman et al., 2003).
Indeed, we found that several components of individual reproductive
investment were repeatable including body mass, egg size and clutch
size. Although there was minor variation in ΔDEE between breeding
attempts this variation itself was not explained by any of the other
measured traits (e.g. body mass, egg size, clutch size) or by
differences in these traits between the two breeding attempts.
Determining the extent to which the repeatability of ΔDEE is robust
under varying breeding conditions would obviously be a priority
for future studies.
Our study adds to the growing evidence for the repeatability of
different measures of energy expenditure, including BMR (Bech et
al., 1999; Labocha et al., 2004; Rønning et al., 2005) (but see Russell
and Chappel, 2007), RMR (Fournier and Thomas, 1999; Vézina
and Williams, 2005) and DEE (Potti et al., 1999; Nespolo and
Franco, 2007) (but see Berteaux et al., 1996). However, we have
also shown that it is important to be able to measure ‘plasticity’ or
change in energy expenditure associated with transitions of
physiological state (e.g. non-breeding to breeding) based on multiple
measurements of the same individual (see McKechnie, 2008). An
increasing number of ecological and evolutionary studies have
highlighted the importance of considering how selection might drive
the evolution of phenotypic plasticity per se not just absolute trait
values (e.g. Piglucci, 2005; Brommer et al., 2008); our study shows
that it will be important to extend this consideration of plasticity to
physiological, endocrinological and metabolic traits (see also
Williams, 2008; Careau et al., 2008).
LIST OF ABBREVIATIONS
BMR
DEE
DLW
RMR
ΔDEE
basal metabolic rate
daily energy expenditure
doubly labelled water
resting metabolic rate
change in DEE
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